Filling Long-Time Gaps of Motion Capture Data

Abstract

We present a general method for data-driven filling of gaps in marker-based mocap data. The novel approach can handle challenging cases, especially if complete marker sets of multiple body parts are missing over a long period of time. Without the need for extensive preprocessing we are able to fix missing markers across different actors and motion styles.